Defect analyzer

ABSTRACT

The present invention provides methods, devices, and systems for analyzing defects in an object such as a semiconductor wafer. In one embodiment, it provides a method of characterizing defects in semiconductor wafers during fabrication in a semiconductor fabrication facility. This method comprises the following actions. The semiconductor wafers are inspected to locate defects. Locations corresponding to the located defects are then stored in a defect file. A dual charged-particle beam system is automatically navigated to the vicinity defect location using information from the defect file. The defect is automatically identified and a charged particle beam image of the defect is then obtained. The charged particle beam image is then analyzed to characterize the defect. A recipe is then determined for further analysis of the defect. The recipe is then automatically executed to cut a portion of the defect using a charged particle beam. The position of the cut is based upon the analysis of the charged particle beam image. Ultimately, a surface exposed by the charged particle beam cut is imaged to obtain additional information about the defect.

[0001] This application claims priority from U.S. Provisional Pat. App.No. 60/425,407, filed Nov. 12, 2002.

TECHNICAL FIELD OF THE INVENTION

[0002] The present invention relates generally to micro-fabricationprocesses, and in particular, the invention relates to defect analysissystems.

BACKGROUND OF THE INVENTION

[0003] Engineers need to analyze defects and other failures duringmicro-fabrication to troubleshoot, adjust, and improve micro-fabricationprocesses. For example, defect analysis is useful in all aspects ofsemiconductor production including design verification diagnostics,production diagnostics, as well as other aspects of microcircuitresearch and development. As device geometries continue to shrink andnew materials are introduced, the structural complexity of today'ssemiconductors grows exponentially. Many of the structures created withthese new materials are re-entrant, penetrating back through previouslayers. Thus, the defects and structural causes of device failure areoften hidden well below the surface.

[0004] Accordingly, defect analysis often requires cross-sectioning andviewing defects on a three-dimensional basis. With the growing use ofcopper conductor devices on semiconductor wafers, better systems capableof performing three dimensional defect analyses are more important thanever. This is because there are more defects that are buried and/orsmaller, and in addition, chemical analysis is needed in many cases.Moreover, structural diagnostics solutions for defect characterizationand failure analysis need to deliver more reliable results in less time,allowing designers and manufacturers to confidently analyze complexstructural failures, understand the material composition, and source ofdefects, and increase yields.

[0005] Unfortunately, the defect characterization provided byconventional systems (e.g., optical inspection tools) is typicallyinadequate. The defect analysis process is typically slow and manual,with a technician individually deciding upon and performing each of thesteps in the analysis. Rather than being integrated into the fabricationprocess, the defect analysis process is more laboratory-oriented thanproduction oriented. In fact, in many fabrication facilities, defectanalysis is performed in a laboratory located outside of the “cleanroom” environment. The results can take too long in being returned tothe fab and the delay in analysis results can result in producing moredefects or shutting down production. When a wafer is taken for detaileddefect analysis, in many cases, the wafer must be discarded after it hasbeen analyzed for fear of contamination and the like, even though only asmall part of the wafer is destroyed by the analysis. With everincreasing wafer sizes and material process complexities, such lossescan result in significant financial hardships.

[0006] Accordingly, what is needed is an improved defect analysis methodand system.

SUMMARY OF THE INVENTION

[0007] The present invention provides methods, devices, and systems foranalyzing defects in an object such as a semiconductor wafer. In oneembodiment, it provides a method of characterizing defects insemiconductor wafers during fabrication in a semiconductor fabricationfacility. The process is partially or fully automated and can be done inthe wafer fabrication facility to provide rapid feedback to processengineers to troubleshoot or improve processes.

[0008] A method of one embodiment comprises the following actions. Thesemiconductor wafers are inspected to locate defects. Locationscorresponding to the located defects are then stored in a defect file.The work piece is aligned in a charged particle beam system and thesystem automatically navigated to the vicinity of the defect locationusing information from the defect file. The defect is identified in acharged particle beam image, and an image of the defect is obtained. Thecharged particle beam image is automatically or manually analyzed tocharacterize the defect. If the defect warrants further investigation, arecipe is determined, either by a user or automatically, for furtheranalysis of the defect. The recipe is then automatically executed. Therecipe will typically entail one or more charged particle beamoperations to remove material and then to form an image the exposedsurface. The position and orientation of the cut or cuts made by thecharged particle beam can be automatically or manually determined basedupon an analysis of the charged particle beam image. Ultimately, one ormore surfaces exposed by the charged particle beam cuts are imaged toobtain additional information about the defect. Defect information canbe uploaded to a yield management system and stored so that informationfrom multiple defects can be analyzed to learn about the fabricationprocess that caused the defects.

[0009] The foregoing has outlined rather broadly the features andtechnical advantages of the present invention in order that the detaileddescription of the invention that follows may be better understood.Additional features and advantages of the invention will be describedhereinafter. It should be appreciated by those skilled in the art thatthe conception and specific embodiment disclosed may be readily utilizedas a basis for modifying or designing other structures for carrying outthe same purposes as the present invention. It should also be realizedby those skilled in the art that such equivalent constructions do notdepart from the spirit and scope of the invention as set forth in theappended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010] For a more complete understanding of the present invention, andthe advantages thereof, the following description is made with referenceto the accompanying drawings, in which:

[0011]FIG. 1A shows a block diagram of one embodiment of a defectanalyzer system of the present invention.

[0012]FIG. 1B shows a defect data flow for the defect analyzer system ofFIG. 1A.

[0013]FIG. 2 shows one embodiment of a screen interface for a defectanalyzer system of the present invention.

[0014]FIGS. 3A through 3N show interface screens and functiondefinitions for one embodiment of a job builder application of thepresent invention.

[0015]FIGS. 3O through 3V, 3X, and 3Y show exemplary screen interfaces,with tables listing controls and descriptions, for one embodiment of aproduct manager module.

[0016]FIG. 3Z shows an exemplary structure for alignment data tree viewnodes of the product manager of FIGS. 3O through 3V, 3X, and 3Y.

[0017]FIG. 4A through 4N show exemplary interface screens and displaysfor one embodiment of a sequencer application of the present invention.

[0018]FIG. 5 shows a block diagram illustrating different use cases thatcan be implemented with one embodiment of a defect explorer.

[0019]FIGS. 6A through 6C show exemplary screen interfaces for oneembodiment of a defect explorer application of the present invention.

[0020]FIG. 7A shows an exemplary window for an auto-die coincidencetool.

[0021]FIG. 7B is a graphical drawing of a die showing an exemplaryauto-die coincidence threshold region.

[0022]FIG. 8A shows an exemplary screen interface for a cal-align tool.

[0023]FIG. 8B is a table of command and field descriptions for thescreen interface of FIG. 8A.

[0024]FIG. 8C shows match results from the cal-align tool.

[0025]FIG. 8D shows an exemplary screen interface returned when nomatches were found.

[0026]FIG. 9A shows an exemplary cross-section tool screen interface.

[0027]FIG. 9B is a table of command and field descriptions for thescreen interface of FIG. 9A.

[0028]FIG. 10A shows one embodiment of a fiducial tool screen interface.

[0029]FIG. 10B is a table of command and field descriptions for thescreen interface of FIG. 10A.

[0030]FIG. 10C shows an exemplary fiducial tool icon in an imagequadrant of a defect analysis screen interface.

[0031]FIG. 10D shows an exemplary information dialog box for oneembodiment of a fiducial tool.

[0032]FIGS. 10E through 10H show various dialog boxes that may appearwith the fiducial tool embodiment of FIGS. 10A through 10D.

[0033]FIG. 11A shows one embodiment of a screen interface for a re-aligntool.

[0034]FIG. 11B shows a table of command and field descriptions for thescreen interface of FIG. 11A.

[0035]FIG. 12A shows a screen interface for one embodiment of an EDStool in a job builder configuration.

[0036]FIG. 12B is a table of command and field descriptions for thescreen interface of FIG. 12A.

[0037]FIG. 12C shows a screen interface for one embodiment of an EDStool in a run-time (sequencer) configuration.

[0038]FIG. 12D is a table of command and field descriptions for thescreen interface of FIG. 12D.

[0039]FIG. 13A shows a screen interface for one embodiment of a getsystem settings tool.

[0040]FIG. 13B is a table of command and field descriptions for thescreen interface of FIG. 13A.

[0041]FIG. 13C shows a screen interface for one embodiment of a grabimage tool.

[0042]FIG. 13D is a table of command and field descriptions for thescreen interface of FIG. 13C.

[0043]FIG. 14A shows a screen interface for one embodiment of a patterntool.

[0044]FIG. 14B is a table of command and field descriptions for thescreen interface of FIG. 14A.

[0045]FIG. 15A shows one embodiment of a pause tool screen interface.

[0046]FIG. 15B is a table of command and field descriptions for thescreen interface of FIG. 15A.

[0047]FIG. 15C shows a run-time screen for the pause tool of FIGS. 15Aand 15B.

[0048]FIG. 15D is a table of command and field descriptions for thescreen interface of FIG. 15C.

[0049]FIG. 16 shows a screen interface for one embodiment of a setsettings tool.

[0050]FIG. 17A shows a screen interface for one embodiment of a sliceand view tool.

[0051]FIG. 17B is a table of command and field descriptions for thescreen interface of FIG. 17A.

[0052]FIG. 18A shows a screen interface for one embodiment of an autoscript tool.

[0053]FIG. 18B is a table of command and field descriptions for thescreen interface of FIG. 18A.

[0054]FIG. 19A shows a screen interface for one embodiment of a systemsettings tool.

[0055]FIG. 19B is a table of command and field descriptions for thescreen interface of FIG. 19A.

[0056]FIG. 20A shows an exemplary screen interface for one embodiment ofan ADR tool.

[0057]FIG. 20B illustrates one embodiment of a routine for implementingthe ADR tool of FIG. 20A.

[0058]FIG. 21 graphically illustrates a wafer with a plurality of diesincluding a die having a defect.

[0059]FIG. 22 is a graphical flow diagram showing one embodiment of anautomatic defect identification process.

[0060]FIG. 23A illustrates different outline refinement methods.

[0061]FIG. 23B is a flow diagram of one embodiment of a routine forrefining an identified defect.

[0062]FIG. 24 shows one embodiment of a defect analysis process.

[0063]FIG. 25 shows a routine for an exemplary defect review use case.

[0064]FIGS. 26A and 26B show a routine for an exemplary defect analysisuse case.

[0065]FIG. 27 shows a routine for an exemplary defect review andanalysis use case.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0066] A. Overview

[0067] The present invention provides partly or fully automatic locationand characterization of microscopic defects in items, such as integratedcircuits or other structures fabricated on semiconductor wafer. Theautomatic characterization of the defect may include steps such asforming an image of the top surface, milling one or more cross sections,forming an image of the one or more cross-sections, performing an x-rayspectroscopy analysis (e.g., energy dispersive spectroscopy, “EDS”) todetermine the type of material present on the surface or in a crosssection, and storing defect characterization data. By being partly orfully automated, the invention can provide rapid feedback to processengineers. Embodiments of the invention can change the defect analysisprocess from a labor intensive, time consuming process performed in alaboratory to a production process that provides timely feedback toprocess engineers for troubleshooting or improving production.

[0068] In one preferred embodiment, the present invention comprises adefect analyzer system particularly useful for automatically analyzingdefects on semiconductor wafers at any point during the waferfabrication. (A preferred system will be compliant with 200 mm and 300mm industry standards and guidelines, including SECS-GEM, and isextendable for processes below 0.13 μm.) Defects are typicallyidentified by a defect inspection system, which typically produces adefect list that includes the approximate position of detected defects.In an embodiment with a defect analyzer system comprising a “dual beam”charged particle beam system having a focused ion beam column and anelectron microscope, the system can automatically align the wafer, andthen automatically navigate to the defect locations specified by theinspection system and process the defects. In addition, the system canautomatically identify the defects and produce and store images andadditional data about the defects. Defects can be re-identified withmore accurate locations and size/shape information determined. Theimages are typically formed using one of the system's charged particlebeams. Having two beams permits different imaging techniques to be used,which can provide more information than a single beam technique. Forexample, information from one beam that is tilted with respect to thework piece will provide different size and shape information about thesite than a beam that is approximately perpendicular to the work. Inaddition the information from the electron beam and ion beam can besignificantly different, and provide information about materials andmorphology of the work piece. Other embodiments could use a single beam,either an ion beam or an electron beam, with the single beam beingeither fixed or tiltable, or two electron beams. In many applications,an electron beam can be used with gases to perform milling or depositionand other operations often done with an ion beam.

[0069] In some embodiments, after images are automatically obtained fora group of defects, a user, such as a wafer fabrication processengineer, views the stored images of the defects off-line and assignsadditional processes to be used to analyze some or all the defects. Theprocess engineer may ignore familiar defects having known causes, butinstruct the system to take a progressive series of cross sectionalimages of some other defects and determine the chemical composition atsome of the cross sections. The wafers can then be re-loaded onto thesystem, which then automatically navigates to the defects again andautomatically performs the prescribed processes to obtain additionalinformation about the defects for the user.

[0070] The specified processes can include, for example, milling one ormore cross sections, taking images of the exposed cross-section,removing one or more layers of material to expose and analyze a buriedlayer, taking physical measurements or performing chemical analyses(such as EDS) on surface or buried layers. In most cases, all thespecified processes are preferably performed automatically, with littleor no user intervention. The results of the analyses are stored andstatistics can be automatically determined based on the multiplemeasurements. The results can also be uploaded into yield managementsoftware.

[0071] In another embodiment, the system navigates to defects on adefect list generated by an inspection tool and then automaticallycharacterizes the defect and determines without operator intervention aset of processes to apply to each defect based upon thecharacterization. For example, the system may take a top-down image andthen analyze the image to automatically characterize the defect.Characterization may include determining an outline and a center foreach defect. For example, the system may determine that a long thindefect should be analyzed by having multiple cross sections cut andimaged perpendicular to its long axis. After the defect is automaticallycharacterized, depending on the defect classification, the system mayperform additional processes, such as cutting one or more cross sectionsand measuring or chemically analyzing the exposed material. For example,an engineer may specify that a certain percentage of a particular classof defects is to have multiple cross sections cut and imaged.

[0072] The simplicity of use of the invention makes it suitable for usewithin a wafer fabrication facility by process engineers or techniciansthat are specialist in the wafer fabrication process and not necessarilyexperts in the charged particle beam systems. Thus, the invention iscapable of providing automated, rapid information to process engineersin the wafer fab.

[0073] A preferred embodiment provides a complete, 3-D defect automationpackage. This preferred embodiment contains integrated navigation, theability to cross section, compositional analysis, advanced gas chemistrydeposition and milling, and imaging. The creation and execution of theanalysis processes, referred to as a “jobs,” are reduced to simple tasksfor engineers and technicians. The hands-off operation of a preferredembodiment allows the user to output consistent and reliable data,including accurate classification, high quality images, 3-D informationof surface or buried features, and chemical data.

[0074] To provide the automatic functionality described above,applicants have developed, among other things, methods to accuratelylocate and re-locate the defect with sufficient accuracy to performmultiple operations using two beams without requiring user intervention.In some embodiments, coincidence of the electron beam and ion beam canautomatically be maintained even when the position of the beams on thework piece is changed, when beam parameters, such as beam current, isadjusted to be appropriate to each defect, or when the environment, suchas the presence or absence of a gas injection needle near the impactpoint, is changed. In some embodiments, the beam impact points are notcoincident, but are separated by a known distance. When the systemswitches from using one beam to using the other, the work piece isautomatically moved by the known distance so that the same point isimpacted by both beams.

[0075] The system automatically relocates and determines the size andshape of the defect, adjusts the image magnification to an appropriatevalue, adjusts the beam parameters, and maintains alignment or realignsthe two beams if required by a change in the beam parameters. Forexample, depending on the size and shape of the defect, an appropriatebeam aperture can be automatically selected to control the beam size andcurrent. More detailed defect characterization information is requiredthan in prior art systems that did not use the characterization todirect focused ion beam operations.

[0076] One method of re-locating and aligning beams is by milling afiducial that can be used to align the beam images, thereby reducingpotential damages caused by aligning the beams on the defect or in caseswhen the defect is altered in the process. The beam alignment can bemaintained when the impact point is moved away from the fiducial by aprobe, such as a capacitive sensor, that maintains a constant distancefrom the beam columns to the top of the wafer, regardless of warp orthickness variation in the wafer. By providing such automatic beamadjustment and alignment, the system can automatically performoperations on different sizes and types of defects without operatorintervention, thereby allowing an automated system to collect andanalyze data for process engineers in a wafer fabrication facility.

[0077] By providing this to process engineers for rapidly analyzingdefects without the need for an actual operator, the system will improveFAB reliability and due to the automatic nature of the data collectioncan dramatically improve the consistency and precision of the data.

[0078] B. System

[0079] With reference to FIG. 1A, in one embodiment, a defect analysissystem 105 is shown connected to remote interface computers 103 throughnetwork 100. Defect Analysis system 105 generally includes defectanalyzer computer (“DA computer”) 107 operably connected to (orintegrated with) a dual beam defect analyzer 109 and database system111. The DA computer 107 and dual beam system 109 use software 108 forimplementing defect analysis and characterization.

[0080] The depicted devices, remote interface computers 103, network100, DA computer 107, dual beam system 109 and database system 111, canbe implemented with any suitable combination of conventional (albeitpossibly modified) equipment, and in many system embodiments, may noteven be included. (For example, the network and network computers willnot be utilized.) Network 100 may be any suitable network configuration,such as a virtual private network (“VPN”), local area network (“LAN”),wide area network (“WAN”) or any combination thereof. Similarly,computers for performing remote interface 103 functions, DA computer 107functions, and database system 111 functions may be any suitablecomputing devices such as desktop computers, laptop computers, PDAs,server systems, mainframes, processing systems made from discretecomponents, and/or combinations of one or more of the same. They canexecute conventional operating systems such as Windows™, UniX™, Linux™,Solaris™ and/or customized, job-specific operating systems.

[0081] In one embodiment, the present invention utilizes a dual beamsystem 109 that uses an ion beam that is either normal or tilted by afew degrees to the plane of the work piece surface and an electron beamhaving an axis that is also tilted, e.g., 52 degrees from the axis ofion beam. In some embodiments, the ion beam and electron beam arecapable of aligning so that the fields of view of both beams arecoincident to within a few microns or less. The ion beam is typicallyused to image and machine the work piece, and the electron beam is usedprimarily for imaging but can also be used for some modification of thework piece. The electron beam will typically produce an image of ahigher resolution than the ion beam image, and it will not damage theviewed surface like the ion beam. The image formed by the two beams canlook different, and the two beams can therefore provide more informationthan a single beam. Such a dual beam system could be made from discretecomponents or alternatively, could be derived from a conventional devicesuch as an Altura™ or an Expida™ system available from FEI Company ofHillsboro, Oreg.

[0082] In the depicted embodiment, software 108 includes user interfacecomponents 112, defect analyzer application/system 113, job builderapplication 115, sequencer application 116, defect explorer application117, and tool components 118. User interface components 112 generateuser interfaces (e.g. screen interfaces) for presenting to userscontrollable access to the functions provided by the defect analyzer,defect explorer, sequencer, and job builder applications, as well as thetool components. The defect analyzer application 113 controls theoverall operation of the defect analyzer system 105. It controls accessto the system and invokes the various other applications and toolcomponents upon receiving requests from users.

[0083] The job builder application 115 allows users to create “jobs”,which define the defect analysis and review tasks to be performed ondefect sites within one or more wafers. A job can be executed by thesequencer application 116, which at least partially automatically causesthe defect analysis system to perform the job tasks on the designateddefect sites. In one embodiment, a software platform is utilized thatsupports Active-X™ and an xPLIB™ automation layer thereby allowingbetter communication between user interfaces and the electronics of thesystem. The defect explorer application 117 allows users to selectivelyreview images and data obtained from defect analysis performed by thedefect analyzer system. The defect explorer application 117 may be runfrom within defect analysis system 105, or it may be run from a separateinterface, remote or otherwise. For example, the defect analyzerapplication 113 could be run on a DA computer 107, which functions as acentral server (possibly located in a FAB, for example) for remoteinterface clients 103, which can access the defect explorer application115 such as from a user's desktop for monitoring the results of thedefect analysis.

[0084] Any suitable software (conventional and/or self-generated)applications, modules, and components may be used for implementingsoftware 108. For example, in one embodiment, the defect analyzerapplication/system is implemented with xP™ defect analysis software,provided by FEI Co. in many of its defect analysis systems. In thisembodiment, software is created for implementing the job builder,sequencer, defect explorer, tool components, and additional userinterface components. Conventional software design techniques can beused to create such software based on the defect analysis andcharacterization principles discussed below.

[0085]FIG. 1B shows data flow between the executing softwareapplications. In this depiction, the job builder 115 and sequencer 116applications are encompassed within the defect analyzer application 113.The defect analyzer application 113 receives defect files as input. Ittransfers the defect file information, along with a path to associatedcaptured images, to the database system 111. The defect explorer 117 hasan interface for searching and selectively viewing defect data andimages from the database system 111. A set of the reviewed images anddata can then be selectively exported to the yield management module 120by placing the generated defect file and images through a configurablefile folder/directory structure 119. In the following sections, thesoftware modules will be discussed in greater detail.

[0086] 1. Defect Analyzer Application

[0087]FIG. 2 shows a screen interface for implementing one embodiment ofa defect analysis application. In this embodiment, the defect analyzerapplication 113, along with the job builder 115, sequencer 116, anddefect explorer 117 applications, is incorporated into an xP™ based dualbeam system provided by FEI Company. The defect analysis application isone functional portion of the system software, which provides amulti-sectioned display with an imaging section 205, a site statussection 215, a tools section 225, a navigation section 235, and adedicated defect analyzer section 245. The purpose and operation of eachof these sections is described in more detail below. From the toolsection 225 and defect analyzer section 245, users can display the jobbuilder interface, the sequencer interface, or the defect explorerinterface. (In the depicted figure, the job builder/recipe builderdisplay is shown.) In one embodiment, an auto-alignment setup page forconfiguring the system for particular job types is also made availableto users. Thus, in order to invoke the defect explorer, sequencer, jobbuilder, or any of the tool components, a user can open the defectanalyzer application 113 and access the desired module via a screeninterface similar to the one shown in FIG. 2. Some or all of thesemodules (e.g., defect explorer) may additionally or separately beaccessible in a stand-alone interface and/or through a differentcomputer device.

[0088] 2. Job Builder

[0089] The Job builder application 115 enables users to build “jobs” foranalyzing defect sites. It also allows users to edit jobs, configure asite (e.g., if an auto-alignment setup application is not provided), andassign a process to a site. Jobs comprise one or more recipes, whichdefine the work to be accomplish at a particular defect site. There arethree basic job structures: (1) same site sequence at each site, (2)different site sequences at different sites, and (3) groups of siteshaving the same process. Such work may include, for example, marking thesite with a fiducial, milling a cross section, or saving an image orcombination. The user builds a job by stringing together and definingrecipes and tools (including predefined system recipes/tools and userdefined recipes/tools). The tools come out of the tool components 118and are associated with (e.g., correspond to or invoke) softwareinstructions that can be initiated and/or executed by the sequencer 116.The sequencer runs jobs created by the job builder. This includeswriting analysis information and transferring stored images to/from adefect analysis file database, which is stored and managed in databasesystem 111. The job builder also includes, in one embodiment, astand-alone product manager module for managing data used by and createdfor jobs and recipes.

[0090] There are at least two types of recipes: a setup recipe involvingmanual or semi-automated tasks such as marking the site with a fiducial,and a process recipe, which involves automated tasks such as milling across section or grabbing an image. Recipes comprise tools, which arethe building blocks in a recipe, i.e., the object used to accomplish aparticular task at a defect site. There are tools for patterning,imaging, moving between die, and establishing beam coincidence, to namea few. A recipe can have any number of tools. Thus, a job, which may bepartially or fully automated, generally has at least one recipe, andeach recipe typically has one or more tools.

[0091] With reference to FIGS. 3A through 3N, an exemplary job builderinterface is depicted. FIG. 3A shows a defect analyzer screen interfacewith a job builder page 302 selected. The job builder applicationcomprises a number of commands and functions for building jobs. Thedepicted command options are listed and described in the table of FIG.3B. Job specific information includes lot number, wafer ID, site list,and'site sequence (or sequences). This information is displayed on theJob page. From the job builder page, a user can select tools and enterdata based on a given defect site, which in one embodiment, is coarselydescribed in a pre-entered defect file. A user can also invoke theproduct manager, which is addressed below.

[0092] In one embodiment, the job builder application has an integratedbut separate recipe builder component. This allows users to buildrecipes from tools, including pre-configured tools, for future use. Therecipes can then be used in the assembly of jobs or in use cases whereall defect sites use the same recipe. Typically, recipes are configuredso that the wafer and defect file are associated with the recipe in thesequencer at runtime. A user can build a recipe from either an existingrecipe or by creating a new one. To build a new recipe, a user (1) opensa new recipe; (2) selects a tool to add to the recipe, (3) configuresthe tool; (4) repeats steps 2 and 3 if desired, and (5) saves the newlycreated recipe. Users may also similarly edit existing recipes. The usercan build a library of recipes that can be then assigned to: (1) allsites in a defect file, and (2) specific defect sites. Any instance of arecipe assigned to a site can be modified. The user will be able tovisit a site, and then decide on the process.

[0093]FIG. 3C shows an insert tool interface. With this interface, theuser adds and removes tools in a job sequence. Each instance of a toolcan have a unique name. During job building, the pre-configured toolsand combination tools can be added to sites individually or in groups.For each site, unique configurations can be defined.

[0094]FIG. 3D shows a job wafer data entry panel. The input data for thejob builder is entered in a dialog box (which can also be used by thesequencer). The operator chooses the defect site filter in this dialogbox. Data entered in the job builder includes, location data identifyingwhere grabbed images will be saved, data defining image annotations, andname data for a particular site sequence. In one embodiment, the jobbuilder inserts logic in jobs so that after analyzing a number ofdefects of a certain class, size, etc., it can stop or take some otheraction defined in the job.

[0095] With reference to FIGS. 3E and 3F, the job builder applicationmay also include a combination filtering feature. This enables users tolimit a review session to certain types of defects and not others byattaching a filter to a job site list. (The term “review session” isused to mean the session for reviewing defects, and can include actionsfrom receiving an initial defect file through locating the defects,characterizing the defects, and further analyzing the defects.) The usercan attach a site filter at any time during a review session. The tablein FIG. 3G lists and describes the various filter interfacecommands/functions. In the depicted- embodiment, to filter defect sites,a user can (1) click “NEW” in the filter dialog box of FIG. 3F to createa new filter file, or click “OPEN” to select an existing filter, and (2)define the new filter or make changes to the existing filter file.Depending on the configuration, only those sites meeting the definedcriteria will be displayed in the wafer map and made available using the“NEXT” and “PREVIOUS” buttons in the “Review Site List” area and listedin the site list in the “Select Site” dialog box.

[0096]FIG. 3H shows a table with site filter criteria parameters thatmay be used for creating filters. A set of filter criteria parametersdefines a filter. Defect sites not meeting the criteria of the activesite filter are excluded from review.

[0097] To specify a filter value, a user can enter a site number, arange of site numbers (e.g., 3-7), or a relation to a site numberindicated by a relational operator followed by a number (e.g., >10). Inthis latter example (>10), the site values 7 and 10 would fail, but10.001 and 13 would pass. Possible relational operators are shown in thetable of FIG. 3I.

[0098] With reference to FIG. 3J, a user may also cause a random subsetof sites to be selected. By using the controls in the depicted dialogbox, a user can specify that only a maximum number of sites or a givenpercentage of sites pass the filter. To specify a random subset, a userselects “ENABLE RANDOM SUBSET,” Selects “Percent” or “Maximum” from thelist box to indicate the type of random subset to be specified; types inthe text box: either the percentage of sites if “Percent” is selected(the site filter would pass, on a random basis, the specified percentageof sites meeting the other filter criteria), or (b) the maximum numberof sites if “Maximum” is selected (the site filter would pass, on arandom basis, no more than the specified number of sites meeting theother filter criteria.

[0099] With reference to FIGS. 3K and 3L, the results of an editedactive site filter may be tested. This allows users to test the resultsof the site filter without having to close the “Edit Active Site Filter”dialog box by clicking “APPLY NOW.” This updates the site counts in the“Test Results” group and also updates the “Review Site-List window.

[0100] With reference to FIG. 3M, an activated site filter may betemporarily disabled. To temporarily disable an active site filter, auser can select “TEMPORARILY DISABLE SITE FILTER,” which causes thedialog box to appear. When a job has been created and saved, theinformation is exported to the database system 111, as configured atDefect Analyzer installation.

[0101]FIG. 3N shows an exemplary job builder site list format forstoring site data. The site data can be made available from aspreadsheet, allowing data to be sorted, filtered, copied, pasted, etc.A user can decide what columns will be in the job builder site list. Thebenefits of this are ease of filtering, sorting, copying, and pastinginformation; and increased information visibility at one time than withother implementations. A user can also specify the path of stage travel.Users can also specify how dies are sorted. For example, users canspecify that dies be sorted: (1) in a serpentine order, which reducesthe total amount of stage travel during review; (2) by increasing rowthen column, which maintains the same general direction of stage motionin each row of dies.

[0102] Users can also control how sites are sorted. Sites are sortedseparately in each die if the user makes the appropriate selection. Forexample, sites may be sorted by: (1) increasing y (axis) then x (axis),which reduces the total amount of stage travel during review; (2)increasing site ID, which maintains a generally increasing trend in siteIDs during review; or (3) using the same order as in defect files, whichmaintains the sites in the same order as in the defect file.

[0103] With reference to FIGS. 3O through 3Z, one embodiment of aproduct manager interface is shown. The product manager interface servesas a control designed as a general purpose interface to theRecipe/Alignment Database, enabling versatile recipe and alignmentreview, training, and creation. It essentially comprises a stand-alonemodule, which can either be launched directly from the Recipe Builderinterface or as an option in the Job Builder interface. In oneembodiment, it has various attributes including manually selected die,compartmentalized alignment training, compartmentalized alignmenttesting, wizard interface support for creating new modules, defectexplorer interface modification capability, convenient copying ofexisting recipe, filters, alignment data, and site maps through a dragand drop interface, easy editing/creation of site maps, easyediting/creation of site filters, and easy editing/creation of sitesequences.

[0104]FIG. 3O shows a screen interface for a recipe manager, FIG. 3Pshows a screen interface for a recipe tree, and FIG. 3Q is a tablelisting their controls with descriptions. FIG. 3R shows a screeninterface for a new setup wizard, FIG. 3S shows an interface forcomponent editors, and FIG. 3T is a table listing their controls withdescriptions. FIG. 3U shows a screen interface for an alignment editor,and FIG. 3V is a table listing its controls with descriptions. FIG. 3Xshows a screen interface for a recipe explorer, and FIG. 3Y is a tablelisting its controls with descriptions. Finally, FIG. 3Z shows anexemplary structure for the alignment data tree view nodes.

[0105] The depicted product manager provides a more database style viewof existing alignments, recipes, site lists, and site maps. Presentedthrough the UI is a standard data grid control that can be sorted butdoes not need to be configurable. The primary purpose of this control isto allow the user access to a repository of alignment and recipeinformation that they can drag and drop into new or existing products.

[0106] 3. Sequencer

[0107] A sequencer performs actions and tool tasks defined in a job ondesignated sites, e.g., according to a designated site/task sequence. Inessence, it provides coordination and communication between sites andthe tools that are being executed upon them. A sequencer within a defectanalyzer may support any combination of the following behaviors: (1) itcan run a job with multiple sites designated; (2) it can run the samesite list and site sequence on different wafers; (3) it can keep dataassociated with a wafer and sites even if multiple jobs have beenexecuted; (4) it can sequentially run different jobs on wafers in acassette; and (5) it can run different site sequences at differentsites. In addition, with some systems, the defect file can be manuallyfiltered or every site designated in a defect file can be processed.

[0108]FIGS. 4A through 4N show screen views of one embodiment of ascreen interface for a sequencer application. FIG. 4A shows a defectanalyzer screen interface with the sequencer page 445 displayed, andFIG. 4B shows a table of command options with associated descriptions.The sequencer page 445 can be accessed through either a toolbar buttonor the “Pages” menu, a dropdown menu located on the upper right of thescreen and allowing a user to select any of several “Pages,” such as aSequencer page or a Job Builder page, for accomplishing a specific task.The user can run a job from the sequencer by clicking the “RUN” button.When the defect analyzer is running, the system may display the livedefect site image in the image quadrant at 405, runtime statusinformation in the status quadrant 415, and navigation wafer map in thenavigation quadrant 425.

[0109] In the depicted figure, the sequencer page 445 has a run timedisplay 447 that appears during sequencer run time. It shows jobprogress, status, and results (pass/processing/fail) of the sites in thejob. The user is able to configure which items from the site list are toappear in the display, which scrolls if necessary. The status of a sitecan be: touched (e.g., visited, processing may or may not have begun,but not finished), untouched (e.g., unvisited, unprocessed),completed/done/processed (e.g., visited and processing completed).Knowing such site status may be important to users for “hot lots” andwhen a user processes multiple wafers in multi-pass sequences that areaborted or partially completed.

[0110] When the sequencer is activated, a wafer map display 425 is shownin the navigation quadrant 425. The current position of the cursor isdisplayed in the lower left corner of the wafer map. The wafer map canuse colors to convey information about a wafer being processed. Forexample, it could use gray for areas outside the wafer (the part of thedisplay area not covered by the wafer), black for the wafer background,green for the die outlines on a patterned wafer, and red for the zerocolumn and row (the die outlines in column zero and row zero of the diepattern). On the wafer map display 427, sites that have a processassociated with them can be visually flagged. Sites meeting the criteriaof the active site filter may be shown on the wafer map. In addition,there can be dynamic color changes for the sites to indicate differentsite sequences, current site (the depicted cross indicates the site thatis currently active), and pass/fail.

[0111] With reference to FIG. 4C, one embodiment of a sequencer set-upprocess is depicted. After a user logs into the defect analysis system451, starts the ion source 452, and sets the tension for both the ionand electron beams 453, it selects the sequencer page at 454 from the“pages” menu. The user next selects the Run command 455, which causesthe “Job Wafer Data Dialog” box 462 to appear at step 456. The job waferdata is entered in this dialog box prior to wafer loading.

[0112]FIG. 4D shows one embodiment of a job wafer data input box alongside FIG. 4E, which depicts a table of its command options and datafields with associated descriptions. In this embodiment, all fields aretypically editable and generally have a list of commonly used values.(This data could also be defined in the job builder.) FIGS. 4F and 4Gshow alternative examples of job wafer data input dialog boxes. With thesystem of FIG. 4G, inventory is performed either automatically by thedefect analyzer, in which case the inventory button is not necessary, ormanually by clicking the INVENTORY button. In some embodiments, theinventory operation checks to see whether a cassette of wafers is loadedonto the defect characterization system. As is made shown by FIGS. 4Fand 4G, this embodiment allows a user to specify automatic processingfor multiple wafers in multiple cassettes. After the inventory has beenperformed, the user selects individual wafers. One click on a populatedslot selects it, changing its display color from blue to active red. Theuser inputs the wafer and lot information. Then the user selects anotherslot. This slot becomes active red and the user inputs its information.The previously selected slot changes to red (not active). Clicking on ared (not active) slot changes it to active. If the user clicks on anactive slot, it is deselected and its display color changes from red toblue. Its information is kept. After information for at least one waferis entered, the RUN button is active. When the user clicks RUN, theinformation for non-selected wafers is purged and Defect Analyzer willproceed with the job. The Information dialog is displayed. If the userclicks CANCEL, all information is purged and the system returns to theprevious step.

[0113] Returning to the sequence process diagram of FIG. 4C at step 456,the user sets the job information, saves the data, and loads a job. Thesequencer operates in both cassette-to-cassette systems with and withoutoptical character recognition (“OCR”). In cassette-to-cassette systemswith OCR, the system can read wafer ID and automatically set the defectfile. The user will typically enter the job file and operator ID, butonly for the first wafer. Additional information can include slot numberand cassette number. If the user does not select a slot, then the topfilled slot is selected. In systems without OCR, the user will normallyenter most if not all of the information. Each wafer is loadedindividually. The user can associate slot numbers with wafer Ids beforerunning a job. All wafers are usually prescanned. That is, there is adefect file for each wafer, and the files are on the system. When thejob is completed, the sequencer unloads the wafer and loads the nextwafer. The system normally loads the first wafer. The user may thenselect the job file, enter operator ID, and select particular slots.He/she then clicks RUN. In contrast, OCR systems may read lot ID andwafer ID. The system then finds the associated defect file from thedatabase system, and the sequencer runs the job.

[0114]FIG. 4H shows a “Defect File” dialog box for selecting the dataformat and a defect file. This dialog box appears when the user clicksDEFECT FILE select button in the in Job Wafer Data Input dialog box.Before opening the defect file, a user selects the data format from thelist box on either the Selected Defect File dialog box or the SelectSite List window, which is depicted in FIG. 4I. In selecting a dataformat, a user deselects any previously selected defect file and removesits contents from the Select Site List (FIG. 4I) window. The user thendeselects the active wafer map. The most recently selected data formatis usually the default. Therefore, it is normally unnecessary toreselect the data format. Selecting the Defect File Initially, thedefect file is the previously selected file. A different defect file maybe selected in any of the following ways: (1) by typing the name of thedefect file in the Defect File text box and then click OK; or (2) byselecting the defect file from the list of files and then clicking OK(or, double-clicking the defect file name). The list contains the namesof defect files contained in the default source directory for theselected data format.

[0115] When a defect file is selected, any previously selected defectfile is deselected and its contents are removed from the Select SiteList window, which displays the contents of the newly selected defectfile. The first site list is automatically selected in the defect file.

[0116]FIG. 4I shows a Select Site List window. From this window, a usercan select the data format if not already chosen, select a defect fileto review if not already chosen, view the defect site lists availablefor review in the defect file, preview the contents of a defect sitelist in a Wafer Map area, and click OK.

[0117] When a defect file is selected, the Select Site List windowdisplays the site lists associated with the selected defect file. TheLot ID and Process ID for the selected defect file also displays.

[0118] There are three columns of information in the site list display(FIG. 4J). These columns include wafer ID, Inspection, and Site Count. Auser can select a desired site list. Descriptions of these columns arelisted in the table of FIG. 4K.

[0119] Returning back to the Sequencer process diagram in FIG. 4C atstep 457, the sequencer next causes an information dialog box 464 to bedisplayed, and the user checks to confirm that the system is ready foruse. The wafer is then loaded (e.g., from a cassette) at step 458. Atdecision step 459, the sequencer determines whether alignment trainingis to occur. This could be done automatically based on job parameters,system, and/or system configuration, or alternatively, it could be basedon user input. If alignment training is to occur, then at step 460, thesequencer initiates alignment training (e.g., via an alignment trainingwizard) and executes the job recipe(s) to perform defect analysis.Conversely, if training is not to occur, then at step 461, the wafer isaligned (e.g., with pattern recognition) and the job is run.

[0120] With reference to FIG. 4L, an Information dialog box displayswhen the user clicks RUN on the Job Wafer Data Input dialog box. Theuser defines the information displayed in this dialog box in the job-builder. This warning box tells the user the initialization stepsneeded (e.g., gas injection system heating, source on, etc.) beforerunning the job. When the user clicks OK, the dialog box closes and thesequencer runs the job. The first step is loading a wafer. If a wafer isalready loaded, the dialog box of FIG. 4M with its included messageappears. When the job completes, a Job Complete box such as that shownin FIG. 4N is displayed.

[0121] 4. Defect Explorer

[0122] With reference to FIG. 5, the defect explorer allows users toperform various tasks in different use cases including reviewing storedimages, reviewing modified defect files, setting tags for revisitingphysical defect sites for processing, and automatic defect relocationvalidation. It also provides a user interface to database system 111 forreviewing data and Images of a defect. It helps user/reviewers navigatethe database system, thereby facilitating convenient review, as well asthe filtering and exporting of relevant site data to, e.g., yieldmanagement systems. In addition, it serves as a tool for reviewing theresults of jobs performed by the defect analyzer.

[0123] The defect explorer can be used by users to export selectedannotated images (single image or multi image file), defect files, andtheir corresponding site information to external systems such as yieldmanagement systems. Images and defect files can be grouped and uploaded,and the database system can be updated with information, e.g., theimages and site details of a wafer that have been exported. A defectfile my also be created having information of the sites selected withlinks to the images of the sites that are associated with it. Theexported data (which can be in any suitable format such as KLARFF) couldrelate to a single wafer or multiple wafers. Defect files may begenerated per wafer-job combination, and the files can be exported toconfigurable directories. Within the screen interfaces, users could thenview all the details that are ready to be exported. In this way, theuser is able to purge data that may not reveal much information aboutthe defect at a particular site. The user can purge the results of DAwith data and corresponding images deleted at job level. Another use ofthe defect explorer is for implementing ADR validation, which isaddressed below in the ADR section.

[0124]FIGS. 6A through 6C show screen interfaces for one embodiment of adefect explorer. In the depicted embodiment, the defect explorerinterface is separate from that of the defect analyzer application. Inthis way, it can readily be run on a remote interface, as well as fromthe defect analyzer system. The defect explorer user interface allowsusers to navigate through the contents of the defect analyzer anddatabase system, and authentication of user credentials is provided.

[0125] With reference to FIG. 6A, users can select a job for reviewbased on any one or combination of search criteria including Lot ID,Wafer ID, and Date. A user can select multiple jobs, and jobs runbetween certain dates for review. For jobs searched or selected based oncertain criteria, corresponding wafer information can be displayed. Theinformation may include Wafer ID, Lot ID, Slot, and Defect file nameinformation. On selection of wafer history, information of the sites inthe selected wafer can also be displayed. Information regarding all thesites on the selected wafer in a job may also be displayed. For example,images corresponding to the selected (single) site can be displayed asthumbnails with appropriate names and in the order in which they aregrabbed by the microscope. The user is able to change the classificationof the defect, and the selected site for review is highlighted.

[0126] Images displayed as thumbnails can be electron beam images, ionbeam images, or they can also be from Slice & View, EDS Spectra, EDSSpectrum and EDS Spot map. Slice and view images of a particular sitecan be displayed like a movie in the order in which they were taken. Theimages can be of any format (e.g. TIF, JPEG, BMP). The selectedthumbnail image can be displayed in full size with annotation, and theuser may be able to save/download one or more slice and view images tothe local machine.

[0127] Users can also add comments for the site based on images. Theadded comments are saved into the database (e.g., in the defect file)corresponding to the site. Comments can be to reclassify the defect,changing the X, Y positions and to relocate the defect. Identity andcomments of the reviewer can also be saved. Users are also able tomodify the comments for a site.

[0128]FIG. 6B shows a wafer site map interface screen from a defectexplorer interface. The wafer map page has all the information about thesites of a selected wafer in a job. This information can be gatheredfrom a defect file or database. Based on the site selected on a wafer,the wafer map section can highlight the corresponding site in adifferent color. Users can tag (mark or list) sites for revisiting orfor future processing. The updated images are to be stored along withthe current images along with comments if any. Tagging can also be usedto define which recipes need to be run on the site for furtherprocessing. Tagging comments of a site may be written into a text fileor into database. A new defect file can be generated having site detailsthat are marked for revisiting. The database system 111 can also beupdated to indicate that site details of a wafer are marked forrevisiting. FIG. 6C shows an interface that allows the user to viewvarious details and to delete a job, export, tag for revisit, or deleteimages.

[0129] 5. Tools

[0130] Some exemplary tool components will now be described. Toolcomponents comprise software for providing a suitable user interface toa user for controlling the particular tool. They also include codeobjects or object calls for controlling the relevant hardware devices(e.g., E-beam, I-beam, stage, gas injection probe) for performing thefunction(s) assigned to the tool.

[0131] a) AutoDieCoincidence

[0132] Because in one embodiment, the electron beam and the ion beam arein the same vertical plane but the one beam is approximately verticaland the other beam is tilted, there is a point at which the two beamswill intersect. By raising or lowering the stage so that the point ofintersection is at the surface of the wafers, the two beams can be madecoincident. Because wafers typically have warp and thickness variations,when the stage is moved in the X or Y direction, the top surface of thewafer will be at a different height from the beam optical columns, andthe beams will no longer be coincident. In a preferred embodiment, asensor, such as a capacitive sensor, measures the distance from thestage to the ion or electron beam column and raises or lowers the stageto maintain a constant difference so that the beams remain coincident.

[0133] The AutoDieCoincidence tool helps a defect analyzer find beamcoincidence at a defect site by reusing coincidence data established forother nearby sites. It is typically used in job builder configurationand sequencer run modes. If a user examines multiple defects within asmall area, processing can be streamlined by instructing the defectanalyzer to reuse the coincidence information at all sites within thatarea.

[0134]FIG. 7A shows an exemplary window that appears when theAutoDieCoincidence tool is selected. It has a Realign Distance Thresholdfield 702, which indicates Radius of a circle within which the defectanalyzer reuses coincidence information. In one embodiment, for desiredresults, a number equal to or greater than the diagonal of one dieshould be used. The following formula describes this condition:

Threshold≧DiePitchX ²+DiePitchY ²

[0135] With reference to FIG. 7B, the defect analyzer ordinarilyestablishes coincidence at the lower left corner, Zd, of a die, D, andrecords the X, Y, and Z coordinates for the point where the beamcontacts the wafer surface. For most wafers, the Z value set at thispoint can be used to establish coincidence at all sites within thespecified radius, or realign distance threshold. When the auto-diecoincidence tool is being used, the defect analyzer uses the measured Zvalue at this point for establishing coincidence on other sites withinthe circle having a radius corresponding to this threshold andpositioned within the die proximal to the measured Zd point. Forexample, in one embodiment, when the auto-die coincidence tool isactive, the system would use the measured Z (height) for establishingcoincidence at all points within the depicted hashed circle, which has aradius that corresponds to the diagonal length of the die, D. Theauto-die coincidence tool is useful whenever processing multiple siteswithin a single die or equivalent area.

[0136] In the depicted embodiment, the auto-die coincidence tool shouldbe run before the fiducial tool. In addition, in some systems, for theauto-die coincidence tool to function correctly, an image may initiallybe trained. The image for both beams can be trained using a navigationtilt function.

[0137] b) CalAlign Tool

[0138]FIG. 8A shows an exemplary screen interface that appears when theCal Align tool is selected, and FIG. 8B is a table of its command andfield descriptions. The CalAlign tool realigns a region of interestafter fiducials are milled, using a stage move or beam shift. The regionof interest is typically aligned in the center of the field of view,which is at an appropriate magnification. For calibration purposes, anadditional option may be available for measuring the offset between thecenter of the image and the center of a fiducial.

[0139] In the depicted embodiment, the CalAlign tool operates in concertwith a Fiducial tool. That is, a fiducial (or equivalent) should bemilled before the Cal Align tool can be used. When used, the patternrecognition parameters set in the Fiducial tool may affect how well theCalAlign tool finds the fiducial.

[0140] The Cal Align tool can be coupled with the Auto Script Tool inorder to gather calibration data. For example, the ion beam may be setto an aperture of 50 pA. The CalAlign tool would measure the location ofthe fiducial. The Auto Script tool changes the aperture and performs anACB (Automatic Contrast and Brightness adjustment). The CalAlign toolnow measures the distance between the image center and the fiducial,whose location will change due to the misalignment of the apertures.This process is repeated, and the collected data can be used to alignthe apertures. In addition the alignment process is used withaccelerating voltage changes, GIS shift, resolution and field of viewshift (between Ultra High resolution for defect characterization andlower resolution for searching), and electron beam spot size shiftcalibrations can be performed in a similar manner. A recipe to find theeucentric height automatically could also be created.

[0141] When DISPLAY MATCH DIALOG is selected, the system displays amatch results in an Image Match window, which is shown in FIG. 8C. Whena number other than 0 is entered in the in the ASSIST TIMEOUT field, adialog box (such as that shown in FIG. 8D) appears when imagerecognition fails. The dialog box remains on screen for the number ofseconds specified in ASSIST TIMEOUT. When this dialog box appears, threeoptions are available: (1) a user can try automatic alignment again byclicking RETRY; (2) if the user desires additional time to realignmanually, it can select STOP TIMER, then center the defect in the fieldof view and click OK.; and (3) if the user desires to terminatealignment, it can click CANCEL.

[0142] c) Cross-Section Tool

[0143]FIG. 9A shows a cross-section tool screen interface, and FIG. 9Bis a table of its command and field descriptions. Controls common toeach group are listed first, followed by those unique to a particulargroup. Using the field of view set by the Fiducial tool, thecross-section tool controls the dual beam apparatus for creatingcomplete cross sections for various processes including metaldeposition, bulk milling, and cross-sectional cleaning. One feature ofthis tool is that it automatically determines appropriate beam settingsbased on relevant task parameters. In the depicted embodiment for thedeposition and cross-section patterns, X and Y dimensions areuser-specified as a percentage of the field of view, and the depth isspecified in microns. For the bulk mill, the width is user-specified asa percentage of the field of view, with the height and depth (Y and Z)calculated by the defect analyzer system.

[0144] The Cross Sectional tool steps through patterns selected in thecross-section tool user interface. Each time an aperture changes or aGIS needle is inserted, the system automatically realigns to thefiducial mark.

[0145] The Y offset is the upper boundary of the cross section. Thedefault location for Y offset is 0 μm, or the vertical center of thefield of view. To redefine the upper boundary of the cross section, auser clicks the Y OFFSET option. The system displays a yellow line inthe image quadrant, which marks the cross-section target line, and thefollowing dialog box.

[0146] To redefine the cross-section target, users can click in theimage quadrant at the point where the cross section is to end. Thesystem displays the bulk mill and cross-section patterns in the imagequadrant and updates CURRENT OFFSET in the cross-section tool interface.

[0147] The bulk cut is a combination of the stair-step pattern and acleanup cut. The stair-step pattern comprises small strips (rectangularboxes). The cleanup cut is performed to remove any re-deposition and toreshape the front edge to facilitate a better cleaning cross-section.

[0148] In the depicted embodiment, in order to properly operate thecross-section tool, the Fiducial tool should be run prior to theCross-section tool. The Fiducial tool determines the size and locationof the defect and sets the field of view. The sizing of the millingpatterns is based on this field.

[0149] d) Fiducial Tool

[0150] After the defect is initially located, it is useful to provideone or more a reference marks so that the defect can be readily foundagain for subsequent processing. A reference mark or “fiducial” ispreferably milled using the ion beam after the defect is initiallylocated. In one aspect of the invention, fiducials containing defectidentification information are implemented. For example, the fiducialcan be made of a size that varies with the size of the defect, that is,a large defect may be marked by a large fiducial. In addition, thefiducial can be made of a shape that is readily distinguishable withimage recognition software and may vary so as to stand out from thesurrounding features. The fiducial is preferably not rotationallysymmetric so that the orientation of the fiducial can be determined uponsubsequent inspection. To be practical, the shape of a fiducial shouldbe millable by an ion beam. Multiple fiducials may be milled if moreaccurate orientation alignment is desired.

[0151] The fiducial allows the user to return to a defect site so, forexample, all defects on a wafer can be characterized using surfaceimaging and after that information is analyzed, a user could return todefects of interest for additional processing. For example, all defectson a die or on a wafer can be located, their outlines determined, and afiducial milled by each defect. An engineer can review the statistics ofthe defects and identify specific defects or classes or defects foradditional analysis. The system can then readily relocate the defect bylocating the fiducial and knowing that the defect itself is positionedat a fixed offset from the fiducial. The size of the defect also allowsthe system to automatically set an appropriate magnification value forimages when the defect is subsequently revisited. (This is desirablebecause changing magnification can change the alignment.) By producingfiducials of different sizes, with the fiducial size corresponding tothe defect size, the beams can be readily aligned at the desiredmagnification when a defect is re-located.

[0152] The fiducial is also useful even if the system does not leave andreturn to the defect site, for example, if the user mills a crosssection immediately after located the defect. The fiducial can be usedto align the ion beam and the electron beam with each adjustment of beamparameters and to adjust the beams for drift. Some of the events thatcan cause a realignment to be desired are described above with respectto the CalAlign tool. Using the defect itself to repeatedly align thebeams would damage the defect making the subsequent characterizationless accurate.

[0153] In many applications aligning the beam is required, for example,when a gas injection needle is inserted or removed. It is common to useion beam deposition to deposit a pad of a protective material, such asplatinum, before milling a cross section. To deposit a material using anion beam, it is necessary to position a gas injection needle close tothe beam impact point on the work piece, so that the precursor gasdeposits on the work piece surface. Inserting and removing the metallicgas injection needle can affect the electric fields near the sample andcan alter the positions of the beams. By providing a fiducial near thedefect, the beams can be aligned on the fiducial before and after thegas injection needle is inserted so that the position of the beamsremain unchanged and the beams remain aligned regardless of the needleposition.

[0154]FIG. 10A shows one embodiment of a fiducial tool window thatappears when the fiducial tool is selected, and FIG. 10B is a tablelisting its command and field descriptions. The Fiducial tool sets thefield of view and mills fiducials for realignment, using auser-specified bitmap as the milling pattern. When the Fiducial tool isrun, the defect analyzer displays the fiducial pattern in the imagequadrant, such as the one shown in FIG. 10C. At the same time, thesystem displays an information dialog box, such as the one shown in FIG.10D, which instructs the user to draw a box around the feature ofinterest. With the arrow tool, a user can draw a box around the featureof interest and then click OK in the dialog box. Once the area isselected, the system recenters the site and sets the magnification asspecified. If the combined parameters for defect size, fiducial size,and fiducial offset are such that the fiducial will overlap the defector extend beyond the field of view, the system warns the user and allowsit to correct the situation. The tool then mills the fiducial, grabs oneimage with each beam, and reestablishes beam coincidence.

[0155] The field of view established by the Fiducial tool, along withimages captured after milling, may subsequently be used by other toolsrun on that site, such as the Realign tool or the cross-section tool.

[0156] When the user clicks “Configure EBeam Realign,” “Configure IBeamRealign,” “Configure EBeam BMP Realign,” or “Configure IBeam BMPRealign,” a Realignment dialog box (FIG. 10E, FIG. 10F, FIG. 10G, FIG.10H) appears. (FIGS. 10E through 10H show the different dialog boxdisplays, depending upon the selected tab.)

[0157] The Realignment dialog box (FIG. 10E, FIG. 10F, FIG. 10G, FIG.10H) contains different panel tabs including a “Train Params” tab, a“Train Region & Origin” tab, a “Run Params” tab, a “Search Region” tab,a “Graphics” tab, and a “Results” tab.

[0158] e) Realign Tool

[0159]FIG. 11A shows an exemplary screen interface for a Realign tool,and FIG. 11B shows a table of its command and field descriptions. TheRealign tool recenters the region of interest after the fiducial(s)is/are milled. This tool can be used to establish beam coincidence andcenter the defect in the field of view. A user can run the Realign toolprior to running any pattern tool to ensure that patterns are preciselylocated in relation to the fiducial mark(s). When the apertures arechanged or whenever it is believed that the fiducial mark may havedrifted, for example, when a GIS needle is be inserted or retracted, therealign tool can also be used to realign the electron beam with stagemoves and realign the ion beam with beam shift.

[0160] f) EDS Tool

[0161] The EDS tool gives the user a method to manually (orautomatically) collect an EDS spectrum, associate that spectrum with thecurrent site, and add it to the database. (This is an extension of thepause tool.) During run mode, the EDS Tool dialog box provides the userwith specific information to collect an EDS spectrum before continuingautomated processing. The EDS tool will typically be used tocharacterize defects where the materials are unknown. In oneimplementation, a default directory is configured for saving the imagesfrom the EDS software. The EDS tool then grabs the spectrum images fromthis directory and puts them into the database.

[0162]FIG. 12A and 12C show exemplary screen interfaces for an EDS toolin job configuration and run-time (sequencer) configurations,respectively, and FIGS. 12B and 12D are tables listing their command andfield descriptions. The job builder interface (FIG. 12A) allows the userto set up the conditions under which the EDS spectrum will be acquired.The user is able to configure ACB, spot/scanning mode, and acceleratingvoltage. The runtime interface (FIG. 12C) is simply a dialog box withinstructions and buttons to continue processing. The text is typicallynot modifiable during runtime. If the user selects cancel, they will bepresented with another dialog asking if they want to fail the site. Ifyes is selected, the site will fail. If no is selected, the user willreturn to the EDS tool runtime interface.

[0163] During runtime, at the prescribed point in the sequence the EDStool runtime interface is displayed. In this way, the user can switch tothe EDS system, acquire a spectrum, and then continue processing. Aspectrum can then be collected, or the site may be failed, which wouldshow in the grid that the site failed, and abort further processing atthat specific site and move to the next site. If the entire job is to beaborted the user can use the “abort” button in the sequencer.

[0164] g) Get System Settings

[0165]FIG. 13A shows a screen interface for a “Get System Settings”tool, and FIG. 13B is a table listing its command and fielddescriptions. The Get System Settings tool lets users save a “snapshot”of system settings. The “Set Settings” tool can then be used to restorethe settings that have been defined. This tool can be used inconjunction with the Set Settings tool to define, then restore, asnapshot of system settings. These tools can be used before and afterany event that is likely to change system settings, such as another toolor a manual change of settings.

[0166] h) Grab Image Tool

[0167]FIG. 13C shows an exemplary screen interface for a “Grab Image”tool, and FIG. 13D is a table listing its command and fielddescriptions. The Grab Image tool is used to collect and save images.The tool sets the appropriate system settings, grabs an image, and savesit. The images can be saved in a predefined folder with a standardnaming convention file name.

[0168] i) MoveDie Tool

[0169] The MoveDie tool moves the stage one die closer to the wafercenter, using the shortest axis of travel. The tool can be used, e.g.,in conjunction with the Get System Settings tool and Set Settings toolto move to an adjacent die, perform a process on that site, then returnto the previous location.

[0170] j) Pattern Tool

[0171]FIG. 14A shows an exemplary screen interface for a “Pattern” tool,and FIG. 14B is a table listing Pattern tool command/filed options withdescriptions. The Pattern tool creates a pattern outside of the toolssuch as cross-sectioning patterns. It can be used for milling,depositing material, or etching.

[0172] When the pattern tool is run, the system automatically realignsto the fiducial mark. When run on a site, the system records the beamshift; realigns the system after a GIS needle is inserted and beforepatterning starts; and returns beam shift to the pre-patterning settingafter patterning is completed and the needle is removed. With typicalembodiments, the fiducial tool should be run on the site before thePattern tool is run. The appropriate GIS should also be heated.

[0173] k) Pause Tool

[0174]FIG. 15A shows a set-up phase “Pause” tool screen interface, andFIG. 15B shows a list of its command/field options and associateddescriptions. FIG. 1 5C shows a run-time phase “Pause” tool screen, andFIG. 15D is a table listing its command/field options with associateddescriptions. The Pause tool lets users manually specify actions outsideof the defect analyzer user interface. Even when a recipe is automated,users can use the Pause tool to allow operator interaction. Users canalso add text to the Pause tool message area to tell the user running ajob to perform an action before continuing automated processing. Userscan define as many Pause dialog boxes as desired. During a job run, thedialog box (FIG. 15c) displays the message defined by the user (e.g.,supervisor user) during setup. The operator user action for the Pausetool is limited to dismissing the pause, either by continuing thesequence or failing the site.

[0175] During a job, the Pause tool dialog box appears at the specifiedpoint in the recipe. If the supervisor configured the Pause tool to timeout during the recipe, the timer will begin the count down. If theoperator user does not stop the count, then the defect analyzerautomatically dismisses the tool, and the job continues.

[0176] The “Pause” tool may be used in conjunction with the Get SystemSettings and Set Settings tools to record, then restore, desired systemsettings. To do this, the System Settings tool can be used to get thesystem state, the Pause tool is launched for manual adjustments. Whenthe task requiring manual adjustments is completed, the user can restorethe named set of system settings using the Set Settings tool.

[0177] l) Set Settings Tool

[0178]FIG. 16 shows an exemplary screen interface for a “Set Settings”tool. The Set Settings tool restores a snapshot of system settingspreviously defined with the Get System Settings tool. The Set Settingsscreen interface has a Get Settings Identifier that indicates the set ofsystem settings to be restored.

[0179] m) Slice and View Tool

[0180]FIG. 17A shows an exemplary screen interface for a “Slice andView” tool, and FIG. 17B is a table listing its command/field optionswith associated descriptions. The Slice and View tool is an advancedmilling and imaging tool. It mills small box patterns and collectsimages, then repeats the process over a selected area to gatherthree-dimensional information about subsurface structures. This tool canbe used for, cross sectioning, locating and reconstructing a feature inthree dimensions, and looking at buried features.

[0181] The Slice and View tool can be used for a variety of applicationsincluding for depositing a protective coating and for milling a bulkpattern, e.g., to remove material that obscures a feature of interest.It can then grab an image with the electron beam, mill a small boxpattern with the ion beam, and grab an electron beam image of theresulting cross-section face. This process of milling and imaging cancontinue until the entire slice area is processed.

[0182] In one embodiment, the slice and view tool can be used once thefiducial tool has been run. The slice and view area is determined by thesize of the defect as defined by the Fiducial tool and indicated by thefiducial itself. Slice and view operations are generally centered on thefield of view that is used by the fiducial tool with the slice depthbeing specified with the slice and view tool. The fiducial mark is alsoused for drift control (re-positioning) and mill location realignment.

[0183] Images can be saved in a desired format (e.g., JPEG) in apredefined folder. When the Slice and View tool is run on a site, thesystem displays milling patterns over the image to indicate wheredeposition and milling will actually occur. The pattern outlines appearsequentially, just as the patterning for that step is about to begin.With this tool, beam settings are determined automatically andconditionally on the fly based upon FOV/defect size and shape.

[0184] n) Auto Script Tool

[0185]FIG. 18A shows an exemplary screen interface for an “Auto Script”tool, and FIG. 18B is a table listing its command/field options withassociated descriptions. The AutoScript tool provides a generalscripting/prototyping tool for quick and easy development of new andunique tools; it also can be used for automating many functions of thedefect analyzer system by allowing users to specify scripts and logfiles. For example, by using this tool, users can write scripts tocontrol milling, scanning, image recognition, stage movement, ion beamcurrent, gas injection, and many other functions.

[0186] o) System Settings Tool

[0187]FIG. 19A shows an exemplary screen interface for a “SystemSettings” tool, and FIG. 19B is a table listing its command/fieldoptions with associated descriptions. The System Settings tool letsusers specify system settings at a specific point in a recipe. The toolcan be used to set up the system prior to running any other tool.

[0188] p) AutoSlice and EDS Tool

[0189] This tool is similar to a combination of the “slice and view”tool and the EDS tool. It provides three-dimensional information aboutthe elemental composition of the defect. At a site where the two beamsare aligned, a buried feature is repeatedly sectioned with the ion beamto expose fresh surfaces. After each section is cut, the electron beamis used to gather EDS elemental data from the exposed surface. This datacan be assembled to provide three-dimensional compositional informationabout the buried feature. The size of the cross section, the beamconditions and the EDS collection parameters can be automatically setbased upon the size and shape of the defect.

[0190] 6. Automatic Defect Relocation

[0191] With reference to FIGS. 20 through 23, one embodiment of anautomatic defect relocation (“ADR”) tool with characterization andrecommendation will now be discussed. The ADR tool locates and verifiesa defect based on its location reported in a defect file and determinesthe defect size. It then updates system parameters to allow other toolsto more efficiently and accurately locates the defect for subsequentoperations. For example, it may re-center the defect in a configurablepercentage of the field of view (“FOV”), which can enable otherautomated relocation and processing jobs.

[0192] a) Automatic Defect Identification

[0193]FIG. 20A shows an exemplary screen interface for an ADR tool. Inbrief, the depicted ADR tool gathers a reference image (in a dieneighboring the die with the defect) and defect image, compares theimages to identify (or isolate) the defect, and centers the detecteddefect, e.g., in a definable percentage of the image prior to exiting.

[0194] The ADR tool can store a report of its results for access by thenext tool that uses it (e.g., in a job recipe sequence). The ADR toolwill typically not execute any stage moves in order to avoidcompromising the accuracy of the relocation. Even a beam shiftcorrection might introduce an unacceptable amount of error. In addition,it is desirable to minimize imaging and thus, additional realigns areavoided. Regardless of how the measured defect position is communicated,additional tools such as the mill pattern tools can exploit informationabout size and orientation prior to attempting a cross section.

[0195]FIG. 20B illustrates one embodiment of an ADR tool routine of thepresent invention. Initially at 2002, the tool records the X, Y, Z stageposition. It next calibrates the stage position in steps 2004-2010. At2004, it determines whether the X stage position is greater or equal to0. If so, then at 2008, it moves the stage one offset position in thenegative direction. conversely, if it is less than 0, it moves the stagein the X direction one positive offset position. At step 2010, itperforms a capacitor probe move.

[0196] Next, at 2012, the tool loads (receives from a defect file) thedie location, defect location, and defect size. At step 2014, it setsmagnification based on the reported defect image size from the defectfile such that the image would be 5 to 10 percent of the FOV. At 2016,the system navigates to a die neighboring that of the defect image andcollects a first reference image, R1. (FIG. 21 shows an exemplarydefective wafer 2102, along with a magnified image site area 2104.) Atdetermination step 2018, if only one reference image is required, thesystem proceeds to step 2020 and moves to the reported defect site totake and store a collected defect image, D. On the other hand, if two(or more) references are to be used, the system navigates to a secondreference site, R2, (which as can be seen is in another neighboring dieto the defect die) to collect and store the second reference image. Itthen proceeds to step 2020 and moves to the defect site, D, to collectand store a collected defect image.

[0197] Next, at 2022, it attempts to identify the actual defect from thecollected defect image using the reference image(s). In one embodiment,pattern recognition algorithms may be used in connection with techniquesof the present invention to identify the actual defect. (Methods foridentifying defects will be discussed in greater detail later inconnection with FIGS. 22, 23A, and 23B.) If the defect is successfullyidentified, then at step 2026, the tool saves and outputs suitabledescriptive information about the defect, and the routine is terminated.For example, it may provide the defect's relative size, location andaspect ratio, along with information about its shape. Conversely, if atstep 2024, it is determined that the defect was not successfullyidentified, then the routine proceeds to search and identify the defect.This may involve such techniques as using a configurable field of viewsearch using magnification changes and/or stage moves. Ultimately theADR tool either outputs suitable descriptive information about thedefect, or it outputs an appropriate status message, e.g., that thedefect was not found. One embodiment of a suitable search/identificationroutine will now be described with regard to steps 2028 through 2040.

[0198] Initially, at step 2028, the routine determines if a search isenabled. If not enabled, at step 2030, it outputs an appropriate statusmessage (e.g., that “the defect was not found”). If the identificationmethod is enabled, however, then the routine proceeds to step 2032 todetermine if a search may be executed (e.g., if it is not exhausted). Ifit cannot be executed, then the tool outputs an appropriate message atstep 2030. Otherwise, it proceeds to step 2034 to initiate anappropriate search. For example, it could implement a magnificationsearch, a spiral search or a combination magnification/spiral search.(The particular search method may be determined automatically based onpredefined criteria, or it could be determined via selection by a userthrough a user interface.) If a magnification search is selected, theroutine proceeds to step 2038 and increments the magnification. If aspiral search is selected, then the routine proceeds to step 2040 andincrements the relative reported defect location in accordance with aspiral pattern. If a magnification/spiral search is selected, then theroutine determines if magnification change options have been exhaustedat step 2036. (In this embodiment, if a magnification/spiral search isselected, the routine, in essence, initially performs a magnificationsearch and then performs the spiral search if necessary.) Ifmagnification is not exhausted, then the routine increments themagnification at step 2038. Alternatively, if magnification adjustmentshave been exhausted, the routine spirally increments the reported defectlocation at step 2040. Whether or not magnification or reported defectlocation are incremented, the routine loops back into the initialsection at step 2016, and the system proceeds as previously describedexcept with a different magnification and/or reported defect location.This continues until either the actual defect is identified andoutputted or until the search is exhausted without the defect beinglocated.

[0199] b) Automatic Characterization

[0200] After the defect is located, it is automatically characterized.Characterization can include forming “top down” images of the surface ofthe defect by using the ion beam. The electron beam can also be used forforming surface images, but the electron beam is typically oriented atan angle to the surface and so the image will be skewed unless correctedin software. Characterization also includes processing the image todetermine the default outline and center. In one embodiment, the outlineof the defect is characterized as a step in characterizing the defectand determining how to cross section the defect. In some embodiments,the outline can be simplified by inflating it to remove edge effects andedge shapes that would overly complicate subsequent calculations.Alternatively, the defect could simply be bounded by a box to determinean outline. In other embodiments, the actual defect outline can be used.The outline data is used to provide information including the size,location, shape, orientation, aspect ratio, etc. of the defect.

[0201] Defects can be sorted based on the outline. For example, afeature having an aspect ratio greater than a specified value, forexample, 20:1, is unlikely to be a defect, so a user can program thesystem to not process those features further. Because the systemcharacterizes the defect for automated processing by the ion beam, moredetailed characterization is required that would be required to merelyidentify the type of defect.

[0202] After the outline of the defect is characterized, the center ofthe defect is located. The center can be located, for example, using acenter of mass calculation over the defect outline, a nodal method asshown in the attached figures, or simply the center of a boundingrectangle. Image contrast can be used a weighing factor in determiningthe center of mass, that is, areas that deviate more in darkness orlightness from the background can be weighted more heavily indetermining the center of the defect. After the outline and center aredetermined, the defect can be classified and further processing, such aswhether to mill a cross section and the cross-sectioning strategy can bedetermined.

[0203] The present invention uses the automatic defect characterizationto provide instructions to a focused ion beam for further processing.For example, a cross section may be cut through the calculated center ofthe defect and extend to the edges of the outline or past the edge ofthe outline by a prescribed amount. The cross-section may be cut, forexample, along the x axis, the y axis, or at a prescribed angle. If theoutline defect indicates that the defect is large, for example, longerthan one micron, a relatively large beam current, such as 5 nA to 10 nA,is used for the creating the cross section and then a smaller beamcurrent, such as 1 nA is used for a fine cut to smooth the cross sectionsurface before viewing. On the other hand, if the defect outlineindicates that the defect is small, such as a defective via, a smallerbeam current, such as 350 pA is used, with a correspondingly smallercurrent used for a polishing cut. A skilled person will readily be ableto determine an appropriate beam current for defects of various sizes.

[0204] The cross-sectioning strategy can be to cut a single crosssection or to cut a series of cross sections, with a scanning electronmicroscope image formed after each cross section, thereby providingthree-dimensional data as a series of slices of the defect. For example,100 cross sections and images can be taken through a defective area tocharacterize the defect. Multiple cross sections are also useful, forexample, when voltage contrast imaging shows that a defect exists alonga conductor, but the location of the defect in unclear. Multiple crosssections can uncover and locate the defect. Each slice can include notonly an image but also other information, such as an EDS analysis of theexposed section.

[0205] With reference to FIGS. 22, 23A, and 23B, an exemplary defectimage identification scheme will now be described. FIG. 22 is a processdiagram showing how a defect may be identified (and/or isolated) from acollected defect image and a reference image. With this scheme, areference image is compared with (subtracted from) the collected defectimage. Initially, however, the collected reference image 2202 may betransformed (“cleaned up”) using a suitable transformation such as anaffine transformation into a transformed reference image 2206. Beforebeing compared with one another, the images may be aligned, ifnecessary, as shown at 2208. The reference image 2206 is then subtractedfrom the collected defect image 2204. The remaining difference image,which includes the defect, is shown at 2210. From here, an outline image2212 may be generated and/or refined using suitable image processingtechniques.

[0206]FIG. 23A illustrates different outline refinement methods. Theinflate outline technique involves minimizing edge effects and improperoutlines. The bounding box method is typically the fastest, simplestmethod. A complex defect outline can also be maintained, with no outlinerefinement methods applied.

[0207]FIG. 23B shows a routine for refining the identified defect imageand/or recommending an image cross-section to be taken. This featureuses the shape and size of a defect to recommend the placement of singleor multiple cross sections. It may be used as an optional advisor to auser, e.g., when performing two-pass, ADR assisted, defect review(discussed later) and as an intelligent agent in an automated tool. Thesoftware for implementing subsequent image processing tasks may be partof the ADR tool or it may be provided elsewhere within the defectanalyzer system. Initially, at 2302, the routine retrieves theidentified defect data as obtained by the ADR tool. This data may definethe defect outline as a rotationally polarized list of data points. At2304, it determines whether or not the defect outline is to be refinedand if so, what type of refinement. In the depicted embodiment, if an“inflate” method is selected, the system performs an inflate outliningalgorithm at step 2306 and moves to decision step 2310 to determine whattype of section centering operation is to be performed. Alternatively,if a different method such as a “bounding box” method is selected, thesystem performs this method at step 2312 and then proceeds to step 2310to determine the section centering operation to be performed. If nooutline refinement is to take place, the routine proceeds directly tostep 2310 to determine the section centering operation that is to occur.In the depicted embodiment, either a nodal center, center of mass, orcenter height centering method may be used. From here, the systemperforms the selected method (nodal 2308, center of mass 2316, centerheight 2314) and proceeds to decision step 2318 and determines whethermultiple sections are to be taken. If they are to be taken, the routineproceeds to decision step 2320 to determine what type of method is to beused. In the depicted embodiment, it performs either a percent-of-defectoperation at 2322 and 2326 or a mass-related operation at 2324 and 2326.Finally, after this is done or if multiple sections are no to be taken,the routine proceeds to step 2328 where it returns the results of thedefect image processing to a designated destination, e.g., user, updateddefect file, defect analyzer component.

[0208] c) Additional ADR Resources:

[0209] A standard set of test structures can be milled onto a wafer totest the relocation accuracy of the ADR implementation. As the ADRcomponent is revised, this wafer can be automatically rerun to provide abaseline measure of relocation accuracy. In addition, an image librarymay also be established. To provide a resource for testing, users cancreate a library of representative and worst-case images.

[0210] i) ADR Validation

[0211] While different use cases generally relating to a defect analysissystem are discussed below, an ADR validation use case will now bedescribed as a feature of ADR. One interesting use of the defectexplorer is for performing automatic defect relocation (“ADR”)validation. (ADR is discussed below.) ADR validation generally involvesperforming an automatic defect relocation operation, reviewing theresults using the defect explorer, and appropriately adjusting the ADRfunction. This may then be followed by altering the defect data andassigning a milling recipe.

[0212] In one particular embodiment, a process for implementing ADRvalidation is performed with the following general tasks: (1) defectsite processing using ADR, (2) site tagging, and (3) tagged siteprocessing and data review.

[0213] With the initial step of defect site processing using ADR, wafersare initially delivered to the DA, either by hand or through factoryautomation. A wafer is then loaded and its designated sites areprocessed. Such processing typically involves (1) navigating to adefect, (2) re-detecting the defect via ADR, (3) acquiring a top-downimage, (4) reporting important process events, and (5) navigating to thenext site t repeat these steps until all of the sites are processed. Thewafer is then typically unloaded.

[0214] The next task of site tagging may be performed either online oroff-line and is done to tag defect sites to be validated. Initially,using the defect explorer, sites are tagged for cross sectioning, autoslice and view, or other processing. From here, the defect outline mayoptionally be resized and relocated using methods discussed below.

[0215] Finally, the tagged sites are processed, and the data isreviewed. To do this, the wafer is loaded, and the system navigates to atagged site. The defect is re-located, and a Cross-Section (XS) or AutoSlice and View (AS&V) function are run. Image data is then acquired andimportant process events are reported (e.g., to the facility host).These steps are then repeated on the other tagged sites until all of thetagged sites have been so processed, and the wafer is unloaded. Finally,either online or offline, the data is reviewed in defect explorer andexported, e.g., to the Yield Manager (YM).

[0216] The ADR validation use case has several advantages. It allows forthe operator to perform Automatic Defect Relocation on numerous defectswithout the necessity to process them. By providing an on- or off-linevalidation step, only defects that are known to be of interest need beprocessed. It also minimizes damage to wafers. Since only defects ofinterest are processed, unnecessary milling is avoided. It alsomaximizes system efficiency. Again, since only the defects of interestare processed, the system process time is optimized. This increases theamount of useful data and maximizes the value of the operator's time.

[0217] ii) Exemplary ADR Image Parameters

[0218] In one embodiment, the following specifications were used for ADRsoftware components. The minimum size of detectable defects is 9 pixels(3×). (Note that in a 30 mm field of view, this corresponds to an ˜100nm defect.) The maximum'size of a detectable defect is nominally <35% offield of view area. With regard to reliability, it should be better than80% success rate for e-beam visible defects. The outlining accuracyshould be such that no less than 80% of the defect pixels are outlined,and no more than 20% of the outlined pixels are not defect pixels. Theprocessing time should be less than 5 seconds, and the system should beable to identify a defect sitting against a featureless background. (Thesystem can be used for bare wafers as well as for wafers havingstructures fabricated thereon.) In addition, the software should be ableto return the complex (vector or equivalent representation) defectoutline. The option to return center of mass, bounding box, androtational orientation would also be available. The software would alsobe able to report a,confidence level for outlined defects. This shouldprovide a qualitative measure of the contrast differences between thedefect pixels and the corresponding pixels in the reference image. Forexample, the software could return outline and confidence data of alllocated defects at least 9 pixels large. Moreover, a limited searchregion may be definable. For example it may be advantageous to notsearch for any defect with 25 pixels of the edge of the defect image.Rotation of the structures at arbitrary angles should also be supported.For these images, the field of view could be at least three times themajor axis of the array's unit cell.

[0219] 7. Training Module

[0220] In one embodiment, before the ADR may be used for locatingdefects on actual defective wafers, a number of wafer specificcalibrations generally need to be trained when a new product isintroduced into the system. The training module allows the user to teachthe system how to align the wafer, that is, how to drive to an alignmentpoint, grab an image, and recognize and find the origin of a pattern.The training module also determines the stage height (from the voltageoutput of the capacitive probe) at which the two beams coincide (theeucentric point), and calibrates a voltage versus height curve so thatthe voltage output of the capacitive sensor can be used to adjust forchanges in the distance between the top surface of the work piece andthe ion or electron column.

[0221] Calibrations performed by the training module can includecalibrating the electron and ion beam images of the die origin at zerodegrees and tilt, the alignment matrix at zero degrees and tilt, and thecapacitive probe set point at zero degrees and tilt. A training modulepreferably allows for individual product specific calibration parametersto be trained and retrained as needed without a complete retraining ofthe entire product (for example, the Cap Probe set point can becalibrated without having to retrain the alignment matrix).

[0222] In typical systems, the training occurs automatically at run-timebut can require mandatory set-up of all calibrations. This isstraightforward for the user, but it locks a user into a completetraining of a product whenever any parameter needs to be trained orretrained. Thus, in one embodiment, an interface is provided that allowsthe user to train or re-train individual calibration parameters at anytime prior to the start of a job. This allows the database to directlyassociate the calibration parameters with the product type, allows asingle calibration parameter to be retrained without a completeretraining, allows complex or difficult to acquire parameters to betrained as needed, and establishes a general model through which othercalibration parameters could be added as the need arises. In concertwith recipe and product validation, a set-up wizard can also be used toguide users through training of multiple parameters.

[0223] The training module runs small, simple trainingcomponents—analogues of the defect analyzer. Tools may be created toguide a user through the calibration. By way of example, a Cap Probecalibration tool might simply throw a dialogue that tells the user tofind the coincident height and click ‘OK’. Perhaps a button could movethe stage to the cap probe height in order to test the calibration, butthere should not be any dependencies on other calibrations for success.FIG. 24 shows a simple interface, which provides a method to launch andstore each calibration routine.

[0224] An advantage of this approach is that a “Wizard” could be easilygenerated to simply string the individual components together. Such atraining sequence could, in turn, be easily generated by a validationstep or as a default new product training. These individual componentscould also be accessed by daily calibration jobs that may require orrecommend certain training for new or out-of-date product parameters.

[0225] C. Defect Analysis Process

[0226]FIG. 24 shows one embodiment of a defect analysis process. Theworkflow methodology includes three basic phases including a job set-upphase 2400, a site set-up phase 2430, and a site process phase 2450. Inthe job setup phase, a user defines parameters (such as specifying adefect file) and creates recipes required for performing a desired job.In the site setup phase 2430, a wafer is loaded and aligned, thendefects are identified and marked with a fiducial so the defect analyzersystem can automatically locate the defect in the site process phase andalign the beams. In the site process phase 2450, the system generallydrives to each defect in a job and runs the process recipe. This phase,as with parts or all of the other phases in certain embodiments, isautomated.

[0227] This workflow is modular and can be broken into its separatephases, which can be run at separate times and by different users. Forexample, one user could define job parameters in the job setup phase2400, and a different user in a different location could mark thedefects in the site setup phase 2430. In the site process phase 2450,the system could be set to operate unattended, perhaps overnight.

[0228] With reference to FIG. 24, the depicted job set-up phase 2400will now be discussed. At decision step 2402, the system determineswhether a pre-existing, saved job is to be run. (This may be based oninput from a user or on system parameters.) If a pre-existing job is tobe run, the system proceeds to the site set-up phase 2430 at step 2432.If a new job is to be created, however, the system proceeds to step 2404and initially trains a wafer. In the depicted embodiment, this involvesnaming a product identifier, training alignment, and loading (selecting)a defect file. At step 2406, a recipe is created. This is normally doneinteractively by a user through the job/recipe builder interface. Atdecision step 2408, the system determines whether only the recipe is tobe run or whether a set-up recipe is to also be run. If a set-up recipeis to also be run, the system proceeds to step 2410 and creates a set-uprecipe. For example, it may invoke a user to interactively create aset-up recipe. From here the system proceeds to step 2412 to create ajob recipe (or process). If at decision step 2408 it was determined thatno set-up recipe is to be processed, then the system directly proceedsto step 2412 to create a job process. From here, the system proceeds tostep 2432 and initiates the site set-up process.

[0229] At step 2432, the system initiates a job and enters a job waferinput. As step 2434, a wafer is loaded and aligned. At step 2436, thesystem drives (or navigates) to a defect. [What exactly is happeningwhen the system “drives” or “navigates” to a defect site?]

[0230] From here, the system proceeds to step 2442 and determines if aset-up recipe exists. If so, it proceeds to step 244 and determines ifthe set-up recipe has already been run. If, however, no set-up recipeexists, the routine proceeds directly to the, site process section 2450and runs the recipe (process) at step 2452.

[0231] Returning back to step 2444, if the set-up recipe has not alreadybeen run, then the system runs the set-up recipe at step 2446. In thisset-up process execution step, a user typically identifies the defectand marks it with an appropriate fiducial. If however, it is determinedthat the set-up process has already been run, then again, the routinewould proceed to the site process section 2450, and the system would runthe recipe. Returning to step 2446, after the set-up recipe is executed(defect is appropriately marked), the routine proceeds to decision step2448 to determine if additional defects exist to be marked. If so, thenthe routine returns to step 2436 and drives to the next defect. Fromhere, it proceeds as previously described. On the other hand, if thereare no additional defects to mark at decision step 2448, then theroutine proceeds to the site processing section 2450 and runs the recipeat step 2452.

[0232] After step 2452 has been executed, i.e., a recipe is run, theroutine proceeds to decision step 2438 to determine if there areadditional defects to be processed. If not, it proceeds to decision step2440 to determine if there are additional wafers to be processed. Ifnot, then the routine ends. On the other hand, if there are additionaldefects, then the routine loops back to step 2434 to load and align thenext wafer to be processed and proceeds as previously described.Returning back to decision step 2438, if there are additional defects inthe loaded wafer, then the routine loops back to step 2436 to drive tothe next defect.

[0233] In the depicted embodiment, the site processing section comprisesthe single step of running the job recipe. Reference may be made to thesequencer section for additional information regarding how the jobrecipe may be run.

[0234] 1. Exemplary Use Cases

[0235] The defect analysis systems of the present invention can be usedin various ways that incorporate parts or all of the process justdescribed. While there are numerous ways to use the system, threeexemplary use cases will be presented. (A use case is simply a way inwhich all or combination of parts of a defect analysis system may beused. For example, the ADR validation process described above is a usecase.) The three basic use cases to be discussed herein are review,analysis, and review/analysis.

[0236] With reference to FIG. 25, a “review” use case routine isdepicted. Initially, at step 2502, the system selects the first defectsite on the first wafer. At step 2504, the system moves the stage tothis defect site. From here, it proceeds to decision step 2506 todetermine if a die change occurred. If so, then the system proceeds tostep 2508 and moves the system to the die origin, realigns, and sets asample to the eucentric height. From here, it moves the system to theactual site at step 2510. It then proceeds to step 2512 to setmagnification and realign to the region of interest (“ROI”) using theADR tool. Alternatively, if there is no die change at step 2506, thenthe system proceeds directly to step 2512 to so set magnification andrealignment. From here, the system grabs a top-down or cross-sectionimage at step 2514. Next, it determines if the final site has beenreviewed at step 2516. If not, then it selects the next site at step2518 and loops back to step 2504 and proceeds as previously described.Otherwise, the system proceeds to step 2520 and unloads the wafer andrepeats the process on the next wafer if appropriate.

[0237] With this use case, the defect analyzer system uses one pass.Defect review is an automated process. It uses the electron beam to grabeither a top-down or cross-section image. The ion beam is not used.Therefore, the system does not drive the stage to each defect sitetwice. The user is only needed to start the process.

[0238]FIGS. 26A and 26B show an exemplary use case routine for analyzingdefects. The process comprises the basic steps of: (1) building a jobwith recipe(s), (2) associating recipes with defects and running a job(e.g., with a sequencer), and (3) use the defect explorer to revisit andanalyze defect sites. Site inspection can vary from site to site. Datareview and tagging of sites can also be done either online or offline.For this use case, the defect analyzer has two passes: site setup andsite process. A two-pass, site-inspection process allows the defectanalyzer to explore defects without a user. After alignment, the firstpass (site setup) starts. The second pass is a fully automated process.The user can see the process happening onscreen and also see milling onthe real-time monitor.

[0239] With reference to FIG. 26A, initially at step 2602, the systemselects a first defect site. At 2604, the stage is next moved to thesite. The system next navigates the site origin at step 2606. At step2608, the beam coincidence tool is initiated. Next, at step 2610, thesystem tool moves the system to the actual site. Next, at step 2612, thetools that are to be run in the recipe are configured. These tools mayinclude realign, grab image, and fiducial milling tools. Next, at 2614,the system settings are saved with the system settings tools. Atdecision step 2616, the system determines if there is an additional sitedefect to setup. If so, then it proceeds to step 2624 to select the nextdefect site and then loops back to step 2604 and proceeds as previouslydescribed. Alternatively, if there is not an additional site left, thenthe routine proceeds to decision step 2618 to see if there is anotherwafer to process. If so, if proceeds to step 2626 to select the nextwafer and loops back to step 2602 to select the first site in the newwafer. From here, the routine proceeds as previously described. If thefinal wafer has been processed, then the routine would go to step 2620and proceed to the next pass (site processing).

[0240] With reference to FIG. 26B, the second pass (site processing)will now be discussed. At 2630, the first defect site is selected. Next,at step 2632, the system parameters are set as they were at the end ofthe first pass. At step 2634, realignment is performed based on thefiducials. Next, from steps 2636 to 2640, the pattern tool is used formetal depositioning, bulk cross sectioning, and/or fine crosssectioning.. At 2642, the cross-section image(s) are grabbed this mayinclude image labeling, naming, and saving. At decision step 2644, thesystem determines if there is another site to be reviewed. If so, thenthe routine selects and drives t the next defect site at step 2646 andloops back to step 2632 to proceed as previously described. On the otherhand, if the defect site is the last site on the wafer to be reviewed,the routine proceeds to decision step 2648 to determine if there isanother wafer to be analyzed. If so, the system selects the next waferat step 2650 and loops back to step 2630 to select the first site on thenew wafer. From here, the routine proceeds as previously described. Ifthe wafer was the last wafer at step 2648, then the wafer is unloaded,and the analysis process terminates.

[0241]FIG. 27 shows a flow diagram of an exemplary review and analysisuse case. At step 2702, the system selects the first defect site. Next,at 2704, the stage is moved to the site's die. From here, the systemproceeds to decision step 2706 to determine if there is a die change. Ifso, then the system moves to 2708 and realigns to die origin. From here,the system proceeds to step 2710 and moves to the actual defect site.From here, it goes to step 2712 and runs the beam coincidence tool.Next, at 2714, the system moves to the actual site. Next, it setsmagnification and realign parameters to ROI using the ADR tool.Alternatively, at decision step 2706, it is determined that there is notsufficient die change, then the system proceeds directly to step 2716and sets magnification and realignment parameters to ROI using the ADRtool. From here, the system proceeds to step 2718 and grabs a top downimage and mills fiducials. Next, in steps 2720 through 2724, the systemruns the pattern tool. The patterning tool may perform metaldepositioning, bulk cross sectioning, and/or closing cross sectioning.Next, at step 2726, the system grabs the cross-section image. Thisincludes image labeling, naming, and saving. At decision step 2728, itchecks to see if there are additional defect sites to review/analyze. Ifso, it selects the next site at step 2730 and loops back to step 2704and proceeds as previously discussed. Conversely, if there is notanother site left in the present wafer, the system loads and processesthe next wafer, if appropriate.

[0242] For this use case, the defect analyzer system has one pass. Thissingle pass process allows the defect analyzer to explore defectswithout a user. The user can see the process happening onscreen and alsosee the milling on the real-time monitor.

[0243] D. Remarks

[0244] Embodiments of the defect analyzer system can provide both defectreview and 3-D analysis capability. It can be a fully automated, defectanalysis tool that can also be used in a semi-automated fashion formanual measurements. X-ray analysis may be a capability of a defectanalysis tool. It can deliver high quality defect classification datafor the sub-0.13 μm processes market including copper dual damascene,chemical mechanical polishing, and high aspect ratio structures.

[0245] The use of defect identifying fiducials provides severaladvantages over conventional fiducial references. For example, theyprovide the ability to readily located the defect with both beams formilling and imaging while minimizing damage to the defect. By combiningboth an ion beam and an electron beam in a single defectcharacterization tool, applicants can provide more information about thedefect than prior art systems. For example, the image from the two beamsmay look different, which can provide information about the mass of theatoms in the work piece and indicate further analysis is desirable.Using the beam that is oriented approximately perpendicular to thesurface can provide more accurate size information than the informationfrom the beam that is tilted. The more accurate information is used tocontrol the subsequent processing, such as cross sectioning.

[0246] For example, if the top down image shows a buried feature, across section can be milled and imaged. If the top down view shows along defect, it can be milled at multiple points. The defectcharacterization can be used to determine settings for the chargedparticle beam columns. For example, if a large defect is detected, alarge aperture can be used in the column to produce a high current.Changes in current typically necessitate realigning the beam. Suchrealignment can be performed easily on the fiducial. In the prior art,defect characterization was not used to control subsequent processing,so the level of detail required was much less.

[0247] The ion beam and the electron beam are preferably accuratelyaligned, that is, that they are imaging the same point. In the priorart, the beams were typically aligned by observing images of the defectfrom both beams and repositioning one beam until the images aligned.This method of aligning is undesirable because when the beams,particularly the ion beam, impinge on the defect, the defect is damaged.On the other hand, with embodiments of the invention, the beams can bephysically aligned, that is, both beams impacting on the same point onthe work piece without moving the work piece, or “computationallyaligned,” that is, the impact points of the beams differ by a knownamount, and the work piece is moved by the known amount when the otherbeam is used. This technique allows the beam columns to be positionedcloser to the work piece, which improves the beam resolution.

[0248] In a preferred embodiment, the alignment procedure begins bymoving the stage so that the nearest die origin is under both beams. Thedie origin is typically marked with a reference mark. The nearest dieorigin may be on a different die than the one the defect is on. Becausethe electron beam axis is tilted with respect to the ion beam axis, theoffset between the ion beam image and the electron beam image can beeliminated by changing the height of the stage. The stage is raised orlowered until the images are coincident. After the stage height isadjusted to make the beams coincident, the stage is moved so that thedefect is in the scan pattern of the beams. Optionally, the beamcoincidence can be further adjusted by observing the fiducial and makinga fine height adjustment of the stage based on the offsets of the imagesof the fiducials. Because wafers can be warped and the height of the topsurface from the beam columns can vary, a capacitive sensor can be usedto maintain a constant height of the top surface of the wafer relativeto the beam column as the stage is moved.

[0249] The invention has broad applicability and can provide manybenefits as described and shown in the examples above. The embodimentswill vary greatly depending upon the specific application, and not everyembodiment will provide all of the benefits and meet all of theobjectives that are achievable by the invention. For example, in one ofthe embodiments described, the electron beam and ion beam are aimed atthe same point on the work piece. In other embodiments, the beams areaimed at different points, and the work piece is translated to theappropriate point to be under the desired beam.

[0250] Although the present invention and its advantages have beendescribed in detail, it should be understood that various changes,substitutions and alterations can be made herein without departing fromthe spirit and scope of the invention as defined by the appended claims.Moreover, the scope of the present application is not intended to belimited to the particular embodiments of the process, machine,manufacture, composition of matter, means, methods and steps describedin the specification. As one of ordinary skill in the art will readilyappreciate from the disclosure of the present invention, processes,machines, manufacture, compositions of matter, means, methods, or steps,presently existing or later to be developed that perform substantiallythe same function or achieve substantially the same result as thecorresponding embodiments described herein may be utilized according tothe present invention. Accordingly, the appended claims are intended toinclude within their scope such processes, machines, manufacture,compositions of matter, means, methods, or steps.

We claim as follows:
 1. A defect characterization system that providesrapid feedback for troubleshooting or improving a micro-fabricationprocess, the system comprising: components for locating defects in asemiconductor wafer, characterizing the defects to determine anappropriate analysis process, and automatically performing thedetermined analysis process.
 2. The system of claim 1, wherein saidanalysis includes exposing one or more buried surfaces in the wafer andtaking an image at the exposed surface.
 3. The system of claim 1,wherein the analysis includes performing a chemical analysis at theexposed surface.
 4. The system of claim 1, in which the defects areinitially found by an inspection system that creates a defect file, thedefect file being used to locate the defects using a high resolutionimaging system also used to characterize the located defect to determinethe analysis process, the analysis process being automatically carriedout by the system.
 5. The system of claim 4, in which the highresolution imaging system includes at least one of an ion beam imagingsystem, scanning electron microscope, and an optical microscope.
 6. Thesystem of claim 1, in which the analysis process includes cuttingmultiple cross sectional portions of the wafer and examining saidportions with an EDS analysis to provide three-dimension elementalinformation.
 7. A method of characterizing defects in wafers duringfabrication in a semiconductor fabrication facility, comprising: (a)inspecting semiconductor wafers to locate defects; (b) storing locationscorresponding to the located defects in a defect file; (c) automaticallynavigating a dual charged-particle beam system to the vicinity defectlocation using information from the defect file; (d) automaticallyidentifying the defect and obtaining a charged particle beam image ofthe defect; (e) analyzing the charged particle beam image tocharacterize the defect; (f) determining a recipe for further analysisof the defect; (g) automatically executing the recipe to cut a portionof the defect using a charged particle beam, the position of the cutbeing based upon the analysis of the charged particle beam image; and(h) imaging a surface exposed by the charged particle beam cut to obtainadditional information about the defect.
 8. The method of claim 7,further comprising automatically adjusting charged particle beamparameters in accordance with the results of the analysis of the chargedparticle beam image before automatically executing the recipe.
 9. Themethod of claim 7, in which analyzing the charged particle beam image tocharacterize the defect includes automatically determining an outline ofthe defect, a center of the defect, or both an outline and a center ofthe defect.
 10. The method of claim 7, in which automaticallyidentifying the defect and obtaining a charged particle beam image ofthe defect includes cutting a fiducial in the work piece near thedefect.
 11. The method of claim 10, in which executing a recipe includeslocating the fiducial, aligning an electron beam and ion beam bysuperimposing the ion beam and electron beam images of the fiducials,and locating the defect by its known displacement from the fiducial. 12.The method of claim 7, in which multiple wafers are inspected andmultiple defects are stored in the defect file, multiple defects areidentified and imaged using the charged particle beam system, recipesare determined for analyzing the defects, and then the defects arere-located on the wafers and the recipes are executed on the multiplewafers.
 13. The method of claim 7, in which analyzing the feature ofinterest includes automatically adjusting the charged particle beamparameters based upon the size and shape of the defect for optimalelemental analysis using EDS or a similar analytic technique.
 14. Themethod of claim 7, in which automatically identifying the defectincludes obtaining a charged particle beam image of an area thought toinclude the defect and obtaining a charged particle beam image of acorresponding area without a defect on a reference die and comparing theimages to identify the defect.
 15. A system for analyzing a defect in anobject, comprising: (a) an electron beam for imaging the object; (b) anion beam for milling the object, wherein the electron and ion beams arecapable of impacting at a desired location of the object; and (c) aprocessing device adapted to be communicatively connected to (i) theelectron beam for controlling it to image a desired image portion, and(ii) the ion beam for controlling it to mill a desired milling portion,and (d) a computer readable media including instructions that whenexecuted by the processing device cause it to control the system forimaging and milling, identifying a defect using information from adefect file, characterizing the defect based upon an image of the defectformed by the electron or ion beam, removing material based upon thedefect characterization to expose a covered portion of the defect, andanalyzing the exposed portion of the defect.
 16. The system of claim 15in which the instructions further include instructions to cause the ionbeam to mill a fiducial in the object near the defect, the fiducialbeing of a physical nature to convey to the system physical informationabout the defect.
 17. The system of claim 15, wherein the ion beam andthe electron beam are aligned to impact the object at overlappinglocations.
 18. The system of claim 15, wherein the ion beam and theelectron beam are aligned to impact the object at different locations,the instructions including instructions to relocate a point on the workpiece surface so that it is under the ion beam or under the electronbeam allowing either beam to be used to image or mill the same point onthe work piece.
 19. A system for analyzing a defect in an object,comprising: (a) an electron beam for imaging the object; (b) an ion beamfor milling the object, wherein the electron and ion beams are capableof impacting at a desired location of the object; and (c) a processingdevice adapted to be communicatively connected to: (i) the electron beamfor controlling it to image a desired image portion, and (ii) the ionbeam for controlling it to mill a desired milling portion, said imagingand milling being based on instructions executed by said processordevice, wherein the instructions include instructions for controllingthe ion beam to mill a fiducial mark in the object proximal to thereported defect, the fiducial being of a physical nature to convey tothe system physical information about the defect.
 20. The system ofclaim 19, wherein the size of the fiducial mark is proportional to thatof the defect thereby allowing the system to determine the relative sizeof the defect by determining the size of the fiducial mark.
 21. Thesystem of claim 19, wherein the instructions include a defect analyzerapplication and tool components for providing to a user defect analysistools including a fiducial tool that allows a user to controllably millthe fiducial.
 22. The system of claim 19, wherein the tool componentsinclude an auto-coincidence tool for achieving beam coincidence byautomatically focusing the electron and ion beams using the fiducialmark.
 23. A defect analysis system for analyzing defects in asemi-conductor wafer, the system comprising: at least two chargedparticle beams for analyzing defects in a wafer; and at least oneprocessing device with software components to perform analysis on thedefect using the at least two charged particle devices; said softwarecomponents when executed providing a job builder, a sequencer, and adefect explorer.
 24. The system of claim 23, wherein the job builderprovides an interface that allows a user to construct a defect analysisprocess to be executed by the sequencer.
 25. The system of claim 24,wherein the job builder interface can access tool components includingslice and view tool components.
 26. The system of claim 24, wherein thejob builder interface can access tool components including a pause toolcomponent that allows the user to define conditions for the analysisprocess to be halted when executed by the sequencer.
 27. The system ofclaim 23, further comprising a database for storing data obtained fromanalyzing the wafer, the database being connected to both local andremote computers having access to said data through the defect explorer.28. A defect analysis system for analyzing defects in a semi-conductorwafer, the system comprising: at least two charged particle beams foranalyzing defects in a wafer; and at least one processing device withsoftware components for performing analysis on defects in the waferusing the at least two charged particle beams, the software componentscausing the system to (1) automatically relocate a previously identifieddefect, (2) determine the size and shape of the defect, (3) adjust imagemagnification of the defect to an appropriate value, (4) adjust chargedparticle beam parameters, and (5) maintain alignment of the at least twobeams as necessitated by changes in beam parameters.
 29. The system ofclaim 28, wherein the software components further cause the system toautomatically select an appropriate beam aperture depending on the sizeand shape of the defect to control the beam size and current.
 30. Adefect analysis system for analyzing defects in a semi-conductor wafer,the system comprising: at least two charged particle beams for analyzingdefects in a wafer having a plurality of dies; a controllable stage forreceiving and positioning said wafer relative to the at least two beams;and at least one processing device with software components to performanalysis on the wafer using the at least two charged particle devices;said software components providing a job builder to allow a user todefine analysis jobs to automatically be performed on the plurality ofdies and a sequencer to execute the defined job and cause the system toanalyze the dies according to the defined job, said job builder allowingthe user to specify a path traveled by the stage for analyzing theseparate dies.
 31. The system of claim 30, wherein a serpentine path ofstage travel for analyzing the separate dies can be specified.